forked from 0xWheatyz/SPARC
Refactor scheduler.py to use the application-level pooled DatabaseClient
Replace the per-invocation DatabaseClient creation in run_scheduled_analysis() with the shared pooled client from SPARC.auth.get_db_client(). This avoids creating a new database connection on every scheduler tick, which could exhaust the connection pool under load. Key changes: - Import get_db_client from SPARC.auth instead of DatabaseClient - Remove manual connect/initialize_schema/close calls - Remove unused SPARC.config import Closes leeworks-agents/SPARC#1658 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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+12
-7
@@ -2,14 +2,17 @@
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Uses APScheduler to periodically re-analyze tracked companies and
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detect significant changes in patent counts.
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The scheduler reuses the application-level pooled DatabaseClient
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(from ``SPARC.auth``) instead of creating its own connection, which
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avoids exhausting the database connection pool under load.
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"""
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import logging
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import os
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from SPARC import config
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from SPARC.analyzer import CompanyAnalyzer
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from SPARC.database import DatabaseClient
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from SPARC.auth import get_db_client
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logger = logging.getLogger(__name__)
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@@ -21,10 +24,13 @@ CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
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def run_scheduled_analysis() -> None:
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"""Re-analyze all tracked companies and check for significant changes."""
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db = DatabaseClient(config.database_url)
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db.connect()
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db.initialize_schema()
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"""Re-analyze all tracked companies and check for significant changes.
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Uses the shared pooled DatabaseClient from ``SPARC.auth.get_db_client()``
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rather than creating a disposable connection, so the scheduler participates
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in the same connection pool as the rest of the application.
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"""
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db = get_db_client()
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tracked = db.list_tracked_companies()
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if not tracked:
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@@ -74,7 +80,6 @@ def run_scheduled_analysis() -> None:
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except Exception as e:
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logger.error("Error analyzing tracked company %s: %s", name, e)
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db.close()
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logger.info("Scheduled analysis complete")
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